Automatic detection of the macula in retinal fundus images using seeded mode tracking approach

Damon W.K. Wong; Jiang Liu; Ngan Meng Tan; Fengshou Yin; Xiangang Cheng; Ching Yu Cheng; Gemmy C.M. Cheung; Tien Yin Wong

doi:10.1109/EMBC.2012.6347103

Automatic detection of the macula in retinal fundus images using seeded mode tracking approach

Damon W.K. Wong^*
, Jiang Liu
, Ngan Meng Tan
, Fengshou Yin
, Xiangang Cheng
, Ching Yu Cheng
, Gemmy C.M. Cheung
, Tien Yin Wong

^*Corresponding author for this work

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

22 Citations (Scopus)

Abstract

The macula is the part of the eye responsible for central high acuity vision. Detection of the macula is an important task in retinal image processing as a landmark for subsequent disease assessment, such as for age-related macula degeneration. In this paper, we have presented an approach to automatically determine the macula centre in retinal fundus images. First contextual information on the image is combined with a statistical model to obtain an approximate macula region of interest localization. Subsequently, we propose the use of a seeded mode tracking technique to locate the macula centre. The proposed approach is tested on a large dataset composed of 482 normal images and 162 glaucoma images from the ORIGA database and an additional 96 AMD images. The results show a ROI detection of 97.5%, and 90.5% correct detection of the macula within 1/3DD from a manual reference, which outperforms other current methods. The results are promising for the use of the proposed approach to locate the macula for the detection of macula diseases from retinal images.

Original language	English
Title of host publication	2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012
Pages	4950-4953
Number of pages	4
DOIs	https://doi.org/10.1109/EMBC.2012.6347103
Publication status	Published - 2012
Externally published	Yes
Event	34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 - San Diego, CA, United States Duration: 28 Aug 2012 → 1 Sept 2012

Publication series

Name	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)	1557-170X

Conference

Conference	34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012
Country/Territory	United States
City	San Diego, CA
Period	28/08/12 → 1/09/12

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

ASJC Scopus subject areas

Signal Processing
Biomedical Engineering
Computer Vision and Pattern Recognition
Health Informatics

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10.1109/EMBC.2012.6347103

Cite this

Wong, D. W. K., Liu, J., Tan, N. M., Yin, F., Cheng, X., Cheng, C. Y., Cheung, G. C. M., & Wong, T. Y. (2012). Automatic detection of the macula in retinal fundus images using seeded mode tracking approach. In 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012 (pp. 4950-4953). Article 6347103 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). https://doi.org/10.1109/EMBC.2012.6347103

Wong, Damon W.K. ; Liu, Jiang ; Tan, Ngan Meng et al. / Automatic detection of the macula in retinal fundus images using seeded mode tracking approach. 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012. 2012. pp. 4950-4953 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

@inproceedings{8fca5d56e46a417c828324e9dc7ef105,

title = "Automatic detection of the macula in retinal fundus images using seeded mode tracking approach",

abstract = "The macula is the part of the eye responsible for central high acuity vision. Detection of the macula is an important task in retinal image processing as a landmark for subsequent disease assessment, such as for age-related macula degeneration. In this paper, we have presented an approach to automatically determine the macula centre in retinal fundus images. First contextual information on the image is combined with a statistical model to obtain an approximate macula region of interest localization. Subsequently, we propose the use of a seeded mode tracking technique to locate the macula centre. The proposed approach is tested on a large dataset composed of 482 normal images and 162 glaucoma images from the ORIGA database and an additional 96 AMD images. The results show a ROI detection of 97.5\%, and 90.5\% correct detection of the macula within 1/3DD from a manual reference, which outperforms other current methods. The results are promising for the use of the proposed approach to locate the macula for the detection of macula diseases from retinal images.",

author = "Wong, \{Damon W.K.\} and Jiang Liu and Tan, \{Ngan Meng\} and Fengshou Yin and Xiangang Cheng and Cheng, \{Ching Yu\} and Cheung, \{Gemmy C.M.\} and Wong, \{Tien Yin\}",

note = "Copyright: Copyright 2013 Elsevier B.V., All rights reserved.; 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 ; Conference date: 28-08-2012 Through 01-09-2012",

year = "2012",

doi = "10.1109/EMBC.2012.6347103",

language = "English",

isbn = "9781424441198",

series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",

pages = "4950--4953",

booktitle = "2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012",

}

Wong, DWK, Liu, J, Tan, NM, Yin, F, Cheng, X, Cheng, CY, Cheung, GCM & Wong, TY 2012, Automatic detection of the macula in retinal fundus images using seeded mode tracking approach. in 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012., 6347103, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, pp. 4950-4953, 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012, San Diego, CA, United States, 28/08/12. https://doi.org/10.1109/EMBC.2012.6347103

Automatic detection of the macula in retinal fundus images using seeded mode tracking approach. / Wong, Damon W.K.; Liu, Jiang; Tan, Ngan Meng et al.
2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012. 2012. p. 4950-4953 6347103 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Automatic detection of the macula in retinal fundus images using seeded mode tracking approach

AU - Wong, Damon W.K.

AU - Liu, Jiang

AU - Tan, Ngan Meng

AU - Yin, Fengshou

AU - Cheng, Xiangang

AU - Cheng, Ching Yu

AU - Cheung, Gemmy C.M.

AU - Wong, Tien Yin

PY - 2012

Y1 - 2012

N2 - The macula is the part of the eye responsible for central high acuity vision. Detection of the macula is an important task in retinal image processing as a landmark for subsequent disease assessment, such as for age-related macula degeneration. In this paper, we have presented an approach to automatically determine the macula centre in retinal fundus images. First contextual information on the image is combined with a statistical model to obtain an approximate macula region of interest localization. Subsequently, we propose the use of a seeded mode tracking technique to locate the macula centre. The proposed approach is tested on a large dataset composed of 482 normal images and 162 glaucoma images from the ORIGA database and an additional 96 AMD images. The results show a ROI detection of 97.5%, and 90.5% correct detection of the macula within 1/3DD from a manual reference, which outperforms other current methods. The results are promising for the use of the proposed approach to locate the macula for the detection of macula diseases from retinal images.

AB - The macula is the part of the eye responsible for central high acuity vision. Detection of the macula is an important task in retinal image processing as a landmark for subsequent disease assessment, such as for age-related macula degeneration. In this paper, we have presented an approach to automatically determine the macula centre in retinal fundus images. First contextual information on the image is combined with a statistical model to obtain an approximate macula region of interest localization. Subsequently, we propose the use of a seeded mode tracking technique to locate the macula centre. The proposed approach is tested on a large dataset composed of 482 normal images and 162 glaucoma images from the ORIGA database and an additional 96 AMD images. The results show a ROI detection of 97.5%, and 90.5% correct detection of the macula within 1/3DD from a manual reference, which outperforms other current methods. The results are promising for the use of the proposed approach to locate the macula for the detection of macula diseases from retinal images.

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DO - 10.1109/EMBC.2012.6347103

M3 - Conference contribution

C2 - 23367038

AN - SCOPUS:84880934895

SN - 9781424441198

T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

SP - 4950

EP - 4953

BT - 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012

T2 - 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012

Y2 - 28 August 2012 through 1 September 2012

ER -

Wong DWK, Liu J, Tan NM, Yin F, Cheng X, Cheng CY et al. Automatic detection of the macula in retinal fundus images using seeded mode tracking approach. In 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012. 2012. p. 4950-4953. 6347103. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). doi: 10.1109/EMBC.2012.6347103

Automatic detection of the macula in retinal fundus images using seeded mode tracking approach

Abstract

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UN SDGs

ASJC Scopus subject areas

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